A practical AI security checklist before you launch an AI feature
Use a short pre-launch checklist to review data, access, abuse, monitoring and response for any AI feature your company ships.
The product team has built an AI summary feature in three weeks and marketing has the launch email ready. The security review is a single call two days before launch. Questions come up that nobody has answered: where customer data goes, how long the model provider keeps it, what stops abuse, and how to switch the feature off if it misbehaves.
AI features often skip normal review because they feel like a small add-on to an existing product. In practice they introduce new data flows, new vendors, new failure modes and new ways for users to misuse the system. A light, repeatable checklist catches the important issues without slowing every launch into a months-long assessment.
Who should own AI security review in a mid-sized company?
Usually the existing security or engineering lead, with input from legal and the product owner. You do not need a separate AI team, but someone must be accountable for sign-off and for tracking findings to closure.
How long should an AI pre-launch review take?
For a typical feature, a few focused working sessions if the checklist is ready and data flows are documented. Features that handle health, financial or identity data, or take actions, deserve deeper testing.
Do we need to test the AI model itself?
Focus on your application: how it uses the model, what data it reaches and what it can do. Review the provider's security documentation and terms, and test misuse scenarios against your own deployment with authorisation.